Remote Director: Data Science Product Leadership

Sedgwick; Boise (ID); Remote; USD 180,000 - 260,000; Full time

Job summary

Sedgwick is seeking a Director of Product Management, Data Science, to define and execute product strategy for a portfolio of predictive models and analytics solutions. You’ll own roadmaps, investment decisions, and delivery accountability, leading product managers and partnering with Data Science, Data Engineering, and architecture leaders.

You’ll ensure governance, model accuracy, and business value, driving scalable, production-ready solutions while aligning with enterprise objectives and

Qualifications

• Bachelor’s degree in a quantitative field is required; advanced degree preferred.
• 10+ years in product management or product strategy with data-science focus.
• Proven track record taking data products from concept to production and measurable impact.
• Experience with agile development and cross-functional leadership.

Responsibilities

• Set product vision and multi-year roadmaps for data-science products.
• Lead portfolio discovery, identify high-value opportunities, and prioritize investments.
• Align model development with business goals, governance, and operational workflows.
• Manage dependencies across data science, engineering, and architecture teams.
• Own portfolio KPIs and drive adoption, value, and sustainability.

Skills

Product management

Data science

Predictive modeling

Machine learning

Agile methodologies

Stakeholder communication

Leadership

Education

Bachelor's degree in Statistics, Data Science, Mathematics, Computer Science, Economics, or related field

Tools

Python

R

SQL

Job description

Sedgwick is seeking a Director of Product Management, Data Science, to define and execute product strategy for a portfolio of predictive models and analytics solutions. You’ll own roadmaps, investment decisions, and delivery accountability, leading product managers and partnering with Data Science, Data Engineering, and architecture leaders.

You’ll ensure governance, model accuracy, and business value, driving scalable, production-ready solutions while aligning with enterprise objectives and